The immune system has long been known to interact with cancer. Beginning in 1891, the orthopaedic surgeon William B. Coley trialled injecting cancer patients with bacterial solutions, attempting to generate strong immune and antitumour responses. But he did not understand the mechanisms underpinning his successes and failures. Our understanding of the relationship between the immune system and cancer has deepened in the intervening time, driving improvements in immunotherapy that have transformed patient outcomes for multiple cancer types.
However, there is still a lot we don’t know. Some cancers, like prostate cancer and breast cancer, have been found to interact with the immune system less than others, and have exhibited mixed, context-dependent responses to immunotherapy. Emerging technologies now let us observe even slight interactions and offer multiple views of the same underlying biology. These views can be combined into a multimodal or multiomic picture, providing new opportunities to understand the relationship between the immune system and cancer. Yet these opportunities also bring evolving analysis challenges.
To address these analysis challenges, I contributed to the development of the tidyomics ecosystem. tidyomics is a collaborative and internationally distributed software project that offers a simple and unified R programming interface for working with biological data across modalities. Using tidyomics and other tools, I combined multiple data modalities to examine the local relationship between the immune cells of the prostate and prostate cancer in 1,374 patients. My findings extend the current view that high-grade prostate cancer forms an immunosuppressive microenvironment, showing specifically that the antitumour action of CD8+ T cells is impaired in this context. I then expanded upon this investigation by studying changes in the peripheral immune system of 134 breast cancer patients, and explored whether distant immune signals in the blood might act as biomarkers of disease progression and metastatic state. Together, this work shows how multiple views of the same data can combine to yield new insights into the relationship between the immune system and cancer.